Transcript Risk Assessment With Sexual Offenders: Approaches

1. Developments in Risk
Assessment: Violence Risk and
Sexual Violence Risk
Kirk Heilbrun, Ph.D.
Drexel University
[email protected]
http://www.drexel.edu/psychology/
research/labs/heilbrun/publications/
2. Goals
• Describe risk assessment (RA) tools
• Describe sexual violence RA tools
• Review empirical studies on violence and
offending in different populations
• Describe scientifically-supported,
scientifically-unsupported, and
controversial uses of risk assessment
3. Important Conceptual
Advances Since 1980
• Short vs. long-term prediction
• Use of term “risk assessment”
• Risk-Need-Responsivity (RNR) and riskneeds assessment
• Particular attention to situational
variables
• Actuarial vs. SPJ vs. unstructured
professional judgment
4. Components of
“dangerousness”
• Risk factors, protective factors – variables
used to predict outcome
• Harm (nature and severity)
• Risk level – probability that harm will
occur
5. Nature of risk factors
• dynamic - changeable via intervention with
individual (treatment, monitoring) or control of
situation (living setting, access to weapons)
– stable
– acute
• static - not changeable via such intervention;
may include personal characteristics (age,
gender) and certain kinds of disorders or
deficits (psychopathy, mental retardation)
6. Legal Contexts
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Criminal responsibility
Sexually Violent Predators
Capital sentencing
Civil commitment
Correctional transfer
Workplace disability
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7. Legal Contexts
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Child custody
Child protection
Juvenile disposition and transfer
Tarasoff
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8. Legal Standards: Risk
Assessment Components
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Nature of risk factors
Level of risk
Severity of harm
Length of outcome period
Context in which harm may occur
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9. Steps in FMHA Risk
Assessment
• Is violence risk part of the evaluation?
• Selection of data sources
• Conducting interviews, administering
measures, and reviewing records
• Interpretation of results
• Communication of findings
• Judicial decision
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10. Forensic Mental Health
Concepts
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Context – domains, FMHA risk assessment
Purpose – why conducting the evaluation
Populations – with whom
Parameters – structuring it
Approach – procedures and specialized
tools
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11. Purpose
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Prediction/classification
Management/intervention planning
Both (risk-needs)
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12. Population
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Age
Gender
Mental health status
Location
Racial/ethnic group
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13. Parameters
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Target behavior
Frequency
Probability/risk category
Settings
Outcome period
Risk and protective factors
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14. Approach
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Actuarial (predictive, risk-needs)
Structured professional judgment (riskneeds)
Anamnestic (needs)
Unstructured clinical judgment
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15. Empirical Foundations and
Limits
Actuarial - formal method using equation,
formula, graph or table to arrive at a
probability or expected value of some
outcome. Uses quantified predictor
variables validated through empirical
research
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16. Empirical Foundations and
Limits
Structured Professional Judgment – uses
specified risk factors, not necessarily from
one dataset. Items are carefully
operationalized so their presence can be
reliably coded. Evaluators then weight the
presence of risk factors and anticipated
intensity of management/treatment needs is
drawing conclusion about risk
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17. Empirical Foundations and
Limits
Anamnestic – process using applied behavior
analytic strategies, seeking detailed
information from the individual regarding
previous behavior similar to the target
outcome. “Individualized” risk factors are
then derived.
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18. Psychosis as Risk Factor
for Violence
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MacArthur Risk Study – psychosis alone not
risk factor; combined with substance
abusehighest risk (slightly higher than SA
alone)
Douglas, Guy & Hart (2009) metaanalysis—psychosis results in 49-68%
increase in odds of violence; moderated by
study design, definition and measurement of
psychosis, and comparison group
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19. Using Actuarial Measures
with Individuals: Debate
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Discussants
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Hart et al. (2007)
Harris & Rice (2007)
Mossman (2007)
Confidence intervals
Wilson’s formula (N=1)
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20. Empirical Evidence on
Actuarial Prediction
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Longstanding area of study (Meehl, 1954)
Meta-analyses
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Bonta, Law, & Hanson (1998)
Gendreau, Goggin, & Smith (2002) – PCL-R vs.
LSI-R
Walters (2003) – PCL-R vs. Lifestyle
Criminality Screening Form
Leistico et al. (2008) – PCL-R
MacArthur Risk Study
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21. Empirical Evidence on SPJ
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13 studies (12 published, 1 dissertation)
11 suggest SPJ judgments are significantly
predictive of violent recidivism
2 did not support this relationship
5/5 studies concluded that SPJ “final
judgment” adds incremental predictive
validity to the actuarial combination of tool
elements
Heilbrun, Douglas, & Yasuhara (2009)
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22. Empirical Evidence on SPJ
vs. Actuarial Approaches
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Limited evidence
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4 studies compared approaches
2 found no differences; 2 favored SPJ in
predictive accuracy
Enhanced structure associated with
actuarial or SPJ approaches increases
accuracy (Monahan, 2008)
Kroner et al. (2005) “coffee can” study—
may be reaching ceiling on predictive
accuracy
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23. Hanson & Morton-Bourgon
sex offender meta-analysis (2009)
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118 samples (N=45,398), 63% unpublished
Best support for actuarial (e.g., Static-99)
and mechanical (e.g., add scales on SVR-20)
approaches
Intermediate support for SPJ approaches,
although SVR-20 stronger
Weakest support for unstructured clinical
judgment
No support for “adjusted actuarial”
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24. Actuarial vs. SPJ Evidence
on Predictive Efficacy
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Depends on tool
Limited evidence comparing them directly
Existing evidence suggests the two
approaches are comparable (Heilbrun,
2009)
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25. Singh/Fazel Metareview (2010)
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Investigated quality and consistency of
findings in reviews and meta-analyses
40 reviews comprising 2,232 studies; nine
main findings
Clinical, actuarial, SPJ: 5/6 meta-analyses
found more support for actuarial than
clinical prediction; 6th meta-analysis found
actuarial and SPJ comparable
Measures: No one measure was consistently
better than all others
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26. Singh/Fazel Metareview (2010)
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Country of study inconclusive—two reviews
found larger effects in U.S., a third
concluded the opposite
Gender: 11/13 reviews concluded that tools
worked comparably in males and females
Ethnicity: 5 reviews found no differences; 3
reported that greater effects resulted from
higher proportion of Whites
Psychiatric populations: 1 meta-analysis
found larger effects in PP; 3 found no diffs
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27. Singh/Fazel Metareview (2010)
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Definitions of outcome: included rearrest,
reconviction, reincarceration, nonaggressive
misconduct, general aggression, physical
violence, verbal aggression, and property
destruction
Length of outcome period: 4/6 metaanalyses found that length of outcome
period was not related to effect size
Risk factors: both static and dynamic risk
factors linked to repeat offending
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28. Singh/Grann/Fazel
Metaregression (2011)
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Systematic review and meta-analysis using 9
risk assessment instruments (HCR-20, LSIR, PCL-R, SORAG, SVR-20, SARA, Static99, SAVRY, and VRAG)
68 studies/25,980 participants/88
independent samples
Highest predictive validity: SAVRY
Lowest predictive validity: LSI-R, PCL-R
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29. Yang/Wong/Coid
Meta-analysis (2010)
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Meta-analysis using 9 risk assessment
instruments (HCR-20, LSI/LSI-R, PCL-R,
PCL-SV, VRS, OGRS, RM2000V, and
GSIR)
28 studies published between 1999-2008
25% of variance related to differences
between tools; 85% of study heterogeneity
was methodological
All 9 were moderately successful and hence
interchangeable except PCL-R with men
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30. Major Developments in
Risk Assessment Tools
• See Otto & Douglas (2009) for overview of
major risk assessment tools
• Prediction
– VRAG, SORAG
– RRASOR, Static-99, Static-2002
– COVR
• Risk Reduction
– Analysis of Aggressive Behavior
31. Major Developments in
Risk Assessment Tools
• Risk-Needs
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HCR-20, SVR-20
RSVP
Stable 2000, Stable 2007
Acute 2000, Acute 2007
VRS, VRS-SO version
LS/CMI
SARA
SAVRY, YLS-CMI, WAJA
32. SAVRY (Borum et al., 2005)
• Structured clinical assessment
• 25 items
• Items are scored -/+
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Historical items
Social/Contextual items
Individual/Clinical items
Protective items
33. SAVRY (Borum et al., 2006)
• Historical Items, e.g.,
– Violence history, non-violent offense history,
violence in the home, early onset of
delinquent behavior, parental criminality,
poor school achievement
• Social/Contextual Items
– Peer delinquency, peer rejection, poor
parental involvement and management, lack
of personal and social support
34. SAVRY (Borum et al., 2006)
• Individual/Clinical Items
– Impulsivity, substance abuse, anger
management problems, psychopathic traits
• Protective Items
– Prosocial peers, strong social support, strong
school commitment, open to intervention,
strong attachment to adult role model
35. YLS/CMI (Hoge & Andrews, 2002)
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Prior and Current Offenses/Dispositions
Family Circumstances/Parenting
Education/Employment
Peer Relations
36. YLS/CMI (Hoge & Andrews, 2002)
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Substance Abuse
Leisure/Recreation
Personality/Behavior
Attitudes/Orientation
37. Level of Service/Case
Management Inventory
(LS/CMI)
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Andrews, Bonta, & Wormith (2004)
Actuarial risk-needs tool, RNR influence
Designed for correctional population
Highly reliable (internal consistency)
Predictive validity comparable to or
better than PCL-R (Gendreau et al.,
2002)
38. Violence Risk Scale (VRS)
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Actuarial risk measure, RNR-based
6 static, 20 dynamic items
Male adult offenders
Good reliability (ICCC > .80)
Good predictive validity (AUC=.75 for
violent reconviction, .72 for nonviolent
reconviction (Wong & Gordon, 2006)
39. Historic-Clinical-Risk
Management (HCR-20)
• Webster et al. (1997)
• SPJ risk-needs tool, risk factors in 3
domains
• Historic: largely static
• Clinical: dynamic
• Risk Management: dynamic
• Validation research has been conducted
predictively, using H domain
40. Violence Risk Appraisal
Guide (VRAG)
• Almost entirely historical and static
factors
• Derived on Canadian sample of mentally
disordered offenders
• Relatively long outcome period (means of
7 and 10 years, respectively)
• Actuarial tool, strength is prediction
41. Classification of Violence
Risk (COVR)
• Based on data obtained from MacArthur
risk project (Monahan et al., 2001) and
additional 2 sites (Monahan, Steadman,
Robbins et al., 2005)
• Chart review, brief interview, computer
entry/scoring, decision tree methodology
• Civil commitment, not criminal
• Good reliability and validity (Monahan,
Steadman, Appelbaum et al., 2005)
42. Sexual Offender Risk
Appraisal Guide (SORAG)
• Quinsey et al. (2006); 14 risk factors (13
static)
• Predictors of recidivism in last decade:
sexual deviance, young age, offending hx,
juvenile antisociality, psychopathy or
personality disorder, alcohol abuse,
extrafamilial victims, abused or lived
apart from parents as a child
43. Static-99
• Hanson & Thornton (1999); Harris et al.
(2003)
• Ten items4 risk levels
• Created merging RRASOR & SACJ-Min
• Highly reliable (inter-rater)
• Predictive validity: AUC values around
.70 (good) (Anderson & Hanson, 2009)
44. Static-2002
• Updated version of Static-99 (Hanson &
Thornton, 2003)
• Limited available research suggests
comparable reliability and validity to
Static-99
• For use with adult males charged w/ or
convicted of offense w/sexual motive
• Official records needed
45. Stable 2000, Stable 2007
• Dynamic risk factors account for
variance beyond static predictors
(Anderson & Hanson, 2009)
• Measures stable dynamic needs (contrast
w/acute) for sexual offenders
• From Sex Offender Needs Assessment
Rating
• Can be combined w/Static-99, Static-2002
46. Acute 2000, Acute 2007
• See Anderson & Hanson (2009)
• Aggregated “acute” measures predicted
better than recent acute measures
• AUC=.77 for Static-99; AUC=.81 for
Static-99 + Stable 2007 (Hanson et al.,
2007)
• Suggests preference for stable factors and
aggregated acute measures in FMHA
47. Sexual Violence Risk-20
(SVR-20)
• Boer et al. (1997)
• SPJ risk-needs tool; structure is
somewhat similar to HCR-20
• Fewer dynamic risk factors
• Three domains
– Psychosocial adjustment
– Sexual offenses
– Future plans
48. Risk for Sexual Violence
Protocol (RSVP)
• SPJ tool
• SVR-20 and RSVP conceptualize risk to
include nature, severity, imminence,
frequency, and likelihood (contrast
w/actuarial)
• Civil and criminal applications, males
18+
• Reliability good to excellent
49. Risk for Sexual Violence
Protocol (RSVP)
• 22 items in 5 domains: sexual violence
hx, psychosocial adjustment, mental
disorder, social adjustment,
manageability
• Limited validity data to date, but looks
promising (Hart & Boer, 2009)
50. Violence Risk Scale-Sexual
Offender version (VRS-SO)
• Adapted from VRS
• 7 static, 17 dynamic items
• Good reliability (ICCC=.74 - .95) (Beyko
& Wong, 2005)
• Good predictive validity (static AUC=.74,
dynamic AUC=.67, total AUC=.72)
(Wong & Olver, 2009)
51. Analysis of Aggressive
Behavior
• See Appendix
• Individualized assessment based on
“anamnestic” approach
• Uses individual’s history to identify risk
and protective factors
• Useful for risk reduction but not
prediction
• Links to treatment planning
52. Research on Violent Behavior
in Individuals w/Mental Disorder
• Increasingly sensitive measures yield
higher base rates
• Particular importance of MacArthur
Risk Study (size, methodology, multi-site)
• Importance of co-occurring substance
abuse as risk factor
53. Research on Violent
Behavior in Sexual Offenders
• Methodological issues
– Measuring outcome
• Nature of behavior
• Accuracy (often underreported)
• Duration of outcome period
54. Base Rates of Sexual
Offending
• Investigators report wide range of
recidivism
• Underreporting is problem
• “adjusted actuarial” debate
• Treatment outcome data
• Outcome rates for Static-99
55. Sexual Offenders: How
Specialized?
• Are we only concerned with sexual
reoffending?
• What about nonsexual offending?
• Nonsexual violence?
56. Adolescent Sexual
Offenders: How Specialized?
• Seto & Lalumiere (2010) meta-analysis of
59 studies comparing male adolescent
sexual offenders (n=3,885) with male
adolescent non-sexual offenders
(n=13,393)
• Results do not support explanation of
general antisocial tendencies
57. Adolescent Sexual
Offenders: How Specialized?
• Seto & Lalumiere (2010) found
empirically supported differences in
sexual abuse hx, exposure to sexual
violence, other abuse or neglect, social
isolation, early exposure to sex or
pornography, atypical sexual interests,
anxiety, and low self-esteem
58. Implications for Risk
Assessment with Sexual Offenders
• Need to compensate for underreporting
• Need to include both stable (risk status)
and changeable (risk state) elements
• Static-99 or SORAG measure risk status
• What assesses risk state? Stable 2007
and Acute 2007 as possibilities.
59. Risk Factors for Sexual
Offending
• See measures of sexual offending risk
discussed to this point
• Add anamnestic, individualized approach
60. Scientifically-Supported
Approaches to Risk Assessment
• Conclusions that individuals scoring
higher on validated actuarial or SPJ tool
are at greater risk for violence
• Actuarial predictions for groups, given
large validation samples and including
margin of error
61. Scientifically-Supported
Uses of Risk Assessment
• Extreme risk categories as more
informative
• Indicating that applying group-based
data to individual or small number of
cases will yield wider confidence intervals
62. Scientifically Unsupported
Uses
• Actuarial prediction strategies without large
derivation and validation samples
• Actuarial prediction strategies applied to
populations that are not part of derivation and
validation samples
• Conclusion that individual has X probability of
future violence without cautions about CIs and
less certainty in individual cases
63. Scientifically Controversial
and/or Untested Uses
• Actuarial prediction strategies with large
derivation and validation samples using
mean probability but not citing margin of
error and greater uncertainty in
individual case
• Assumption that there are reliable,
known probability estimates robust
across samples, even at group level
64. Forms of Risk Communication
• Prediction-oriented
– Probability (“10% likelihood”)
– Frequency (“10 individuals in 100”)
– Include confidence intervals
• Management-oriented
• Risk-needs
65. Justifications for Importance
of Risk Communication
• Significant demand for risk assessment
• Likely increase in this demand in the future
• Link between risk assessment and decisionmaking
• Enhances better-informed legal decisionmaking
• Serious impact of risk-relevant decisions
66. Preface to Risk Assessment
Report
• Prediction, Management, and Risk-Needs
• Can be adapted for own practice
67. Testimony on Risk
Assessment
“Will he be violent?”
– Refer to written statement
– “It depends.”
– Respond in probability, not yes or no
• “Is he dangerous?”
– Refer to written statement
– Describe target behavior and time period
– Ask to clarify meaning of “dangerous”